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用于主动声纳目标深度分类的波导不变自适应匹配滤波器。

A waveguide invariant adaptive matched filter for active sonar target depth classification.

机构信息

NATO Undersea Research Centre, Viale San Bartolomeo 400, La Spezia 19126, Italy.

出版信息

J Acoust Soc Am. 2011 Apr;129(4):1813-24. doi: 10.1121/1.3557041.

Abstract

This paper addresses depth discrimination of a water column target from bottom clutter discretes in wideband active sonar. To facilitate classification, the waveguide invariant property is used to derive multiple snapshots by uniformly sub-sampling the short-time Fourier transform (STFT) coefficients of a single ping of wideband active sonar data. The sub-sampled target snapshots are used to define a waveguide invariant spectral density matrix (WI-SDM), which allows the application of adaptive matched-filtering based approaches for target depth classification. Depth classification is achieved using a waveguide invariant minimum variance filter (WI-MVF) which matches the observed WI-SDM to depth-dependent signal replica vectors generated from a normal mode model. Robustness to environmental mismatch is achieved by adding environmental perturbation constraints (EPC) derived from signal covariance matrices averaged over the uncertain channel parameters. Simulation and real data results from the SCARAB98 and CLUTTER09 experiments in the Mediterranean Sea are presented to illustrate the approach. Receiver operating characteristics (ROC) for robust waveguide invariant depth classification approaches are presented which illustrate performance under uncertain environmental conditions.

摘要

本文针对宽带主动声纳中从底部杂波离散体中分辨水柱目标的深度问题展开研究。为了便于分类,该文利用波导不变量特性,通过对宽带主动声纳数据的单次探测的短时傅里叶变换(STFT)系数进行均匀子采样,推导出多个快照。使用子采样的目标快照来定义波导不变谱密度矩阵(WI-SDM),这允许应用基于自适应匹配滤波的方法进行目标深度分类。通过使用匹配观察到的 WI-SDM 到从模态模型生成的与深度相关的信号副本向量的波导不变最小方差滤波器(WI-MVF)来实现深度分类。通过添加从信号协方差矩阵中平均得出的环境扰动约束(EPC)来实现对环境失配的稳健性,这些 EPC 是针对不确定信道参数得出的。为了说明该方法,文中给出了来自地中海的 SCARAB98 和 CLUTTER09 实验的仿真和实际数据结果。文中还给出了稳健的波导不变深度分类方法的接收机操作特性(ROC)曲线,这些曲线说明了在不确定环境条件下的性能。

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